DocumentCode
3309243
Title
Generating Optimum Number of Clusters Using Median Search and Projection Algorithms
Author
Suresh, Lalith ; Simha, Jay B. ; Veluru, Rajappa
Author_Institution
CSE Dept., CITech, Bangalore, India
fYear
2010
fDate
20-21 June 2010
Firstpage
274
Lastpage
276
Abstract
K-means Clustering is an important algorithm for identifying the structure in data. In this work, a novel approach to seeding the clusters with the latent data structure is proposed. This is expected to minimize: the need for number of clusters apriory and time for convergence by providing near optimal cluster centers. Also these algorithms are tested on the latest standards for data warehouses – the column store databases.
Keywords
Clustering algorithms; Computer architecture; Convergence; Data structures; Data warehouses; Databases; Programming profession; Projection algorithms; Shape measurement; Testing; Clustering; DBMS; Median Projection; Median Selection; SQL; k-means Algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Advances in Computer Engineering (ACE), 2010 International Conference on
Conference_Location
Bangalore, Karnataka, India
Print_ISBN
978-1-4244-7154-6
Type
conf
DOI
10.1109/ACE.2010.95
Filename
5532825
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